Abstract: Some embodiments of the present disclosure relate to systems and methods including generating, by infrared spectroscopy, spectra data identifying quantities and associated wavelengths of radiation absorption for each of a plurality of wine samples as determined by the infrared spectroscopy; converting the spectra data for each wine sample to a set of discretized data; transforming the discretized data into a visual image representation of each respective wine sample, the visual image representation of each wine sample being an optically recognizable representation of the corresponding converted set of discretized data; and storing a record including the visual image representation of each wine sample in a memory.

Abstract: Some embodiments of the present disclosure relate to systems and methods including acquiring an image including an indication of at least one wine; identifying, by optical character recognition, the at least one wine in the acquired image; correlating each of the identified at least one wines to a visual image representation of each wine; and executing a trained computer vision classification system using the visual image representation of each of the identified wines and labeled visual image representations of at least one wine associated with a user flavor profile including at least one classification as inputs to generate an output including, for each of the identified wines, an indication of whether the identified wine corresponds to the at least one classification associated with the user flavor profile.

Abstract: Embodiments of the present invention relate to a platform for controlling production and distribution of consumable items based on machine learning processes derived from chemical profiles of the consumable items.

Abstract: Embodiments of the present invention relate to a platform for controlling production and distribution of consumable items based on machine learning processes derived from chemical profiles of the consumable items.

Abstract: Embodiments are directed to labeling and distributing products having multiple versions while providing correlation of user ratings with a received product version on a per user basis.

Abstract: A method of custom labeling products in which users specify, via a purchasing interface, product label images in correspondence with products. A label group is generated for each of the users. The label group includes an indicator label image providing a purchase identifier and product identifiers, and the product label images arranged in a sequence specified by the product identifiers. The label groups are printed to produce printed label groups. The printed label groups are transferred to a labeling machine. A conveyor system is controlled to release, for each of the printed label groups, the sequence of the products specified by the product identifiers. Printed product labels of each of the printed label groups are applied to the corresponding sequence of the products.

Abstract: Embodiments are directed to labeling and distributing products having multiple versions while providing correlation of user ratings with a received product version on a per user basis.

Abstract: Embodiments of the present invention relate to a platform for controlling production and distribution of consumable items based on machine learning processes derived from chemical profiles of the consumable items.

Abstract: A method of custom labeling products in which users specify, via a purchasing interface, product label images in correspondence with products. A label group is generated for each of the users. The label group includes an indicator label image providing a purchase identifier and product identifiers, and the product label images arranged in a sequence specified by the product identifiers. The label groups are printed to produce printed label groups. The printed label groups are transferred to a labeling machine. A conveyor system is controlled to release, for each of the printed label groups, the sequence of the products specified by the product identifiers. Printed product labels of each of the printed label groups are applied to the corresponding sequence of the products.